The sensation of groove engages motor and reward networks
Bibliographic record
Abstract
The sensation of groove has been defined as the pleasurable desire to move to music, suggesting that both motor timing and reward processes are involved in this experience. Although many studies have investigated rhythmic timing and musical reward separately, none have examined whether the associated cortical and subcortical networks are engaged while participants listen to groove-based music. In the current study, musicians and non-musicians listened to and rated experimentally controlled groove-based stimuli while undergoing functional magnetic resonance imaging. Medium complexity rhythms elicited higher ratings of pleasure and wanting to move and were associated with activity in regions linked to beat perception and reward, as well as prefrontal and parietal regions implicated in generating and updating stimuli-based expectations. Activity in basal ganglia regions of interest, including the nucleus accumbens, caudate and putamen, was associated with ratings of pleasure and wanting to move, supporting their important role in the sensation of groove. We propose a model in which different cortico-striatal circuits interact to support the mechanisms underlying groove, including internal generation of the beat, beat-based expectations, and expectation-based affect. These results show that the sensation of groove is supported by motor and reward networks in the brain and, along with our proposed model, suggest that the basal ganglia are crucial nodes in networks that interact to generate this powerful response to music.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".